东北大学学报(自然科学版) ›› 2009, Vol. 30 ›› Issue (6): 769-772.DOI: -

• 论著 • 上一篇    下一篇

复杂场景下运动车辆实时动态自适应检测方法

吴成东;刘濛;张云洲;楚好;   

  1. 东北大学信息科学与工程学院;
  • 收稿日期:2013-06-22 修回日期:2013-06-22 出版日期:2009-06-15 发布日期:2013-06-22
  • 通讯作者: Wu, C.-D.
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(60874103)

Dynamic real time adaption detection algorithm for moving vehicles in complex scenes

Wu, Cheng-Dong (1); Liu, Meng (1); Zhang, Yun-Zhou (1); Chu, Hao (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110004, China
  • Received:2013-06-22 Revised:2013-06-22 Online:2009-06-15 Published:2013-06-22
  • Contact: Wu, C.-D.
  • About author:-
  • Supported by:
    -

摘要: 针对复杂交通场景中运动车辆检测方法存在的局限性,提出了一种基于自适应背景与改进动态阈值相结合的运动检测算法.基于当前帧与背景相减得到的差分图像,利用自适应阈值选取方法分别对差分图像的三个颜色通道进行二值化,从而实现运动目标的精确检测.根据检测结果,采用中值更新策略实现背景图像的实时更新.实验结果表明,该算法可以从复杂交通场景图像序列中有效地检测出运动目标.而且算法计算量小,具有良好的鲁棒性与实时性品质指标,能够很好地满足智能交通监控系统中运动车辆实时检测技术要求.

关键词: 运动车辆, 运动目标检测, 动态阈值, 智能交通

Abstract: An algorithm based on adaptive background and improved dynamical threshold is proposed to solve the problem of the limitation of current detection methods of moving vehicle in complex scenes. Obtaining the difference image by the substraction between present frame and background, the precision detection of moving objects is implemented through binaryzing the three different color channels of the difference image by selecting adaptive threshold values. According to the detected objects, an updating strategy by mean values is introduced to achieve real-time update of background. Experimental results of outdoor image sequences demonstrated that the proposed algorithm can effectively detect moving objects in complex traffic scenes, and what's more its computation cost is reduced with higher robustness and real-time performance provided, thus meeting the requirements of real-time detection of moving vehicles in intelligent transportation surveillance system.

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